Background. Recent evidence points to the importance of the initial colonization of the human body with microorganisms-the establishment of the microbiome-as a determinant of health outcomes throughout life. The metagenomic technological advances available for characterizing the human microbiome across large cohorts at multiple time points are rapidly out-pacing the computational tools needed to clarify patterns of assembly of the microbiome and investigate connections between observed patterns and health and disease. Network-based methods have immense promise for filling this critical gap, but there are major limitations in the available suie of network analytic tools. The identification of clinically relevant patterns in biological network, and in particular, temporally evolving networks, urgently requires novel methodological approaches. Candidate. Dr. Hoen is a computational epidemiologist mentored by a multidisciplinary team within the Institute for Quantitative Biomedical Sciences (iQBS) and the Geisel School of Medicine at Dartmouth College. With her PhD in infectious disease epidemiology at Yale University and her postdoctoral training in the Children's Hospital Boston Informatics Program/Harvard Medical School, she is extremely well qualified to successfully accomplish her proposed research and career development plan and transition to independence as a scientist in biomedical informatics with the support of this award. Dr. Hoen has an established, productive research background that has resulted in 26 peer-reviewed publications on her interdisciplinary research. Environment. iQBS and the Geisel School of Medicine offer the ideal environment for the proposed career development and research. A collegial intellectual environment, at the core of which is Dr. Hoen's exemplary team of mentors and advisors is bolstered by numerous state-of-the-art research centers and core facilities, including a world-class supercomputing facility. Regular research seminars address current advances in biomedical informatics, genomics and biostatistics, and frequent lecture series in informatics, genomics and medicine attract leading investigators from around the world. Career Development Plan. The goal of this proposal is to gain mentored research experience and career development activities in order to advance Dr. Hoen' career into that of an independent researcher in biomedical informatics. Dr. Hoen's previous research has focused on computational studies of the distribution and determinants of infectious disease risk. She has experience in the analysis of microbial genomic data (doctoral training) and in public health informatics (postdoctoral training). The proposed career development activities and mentored research experience would take Dr. Hoen's expertise to a new level in two distinct ways: (1) by providing her mentored research experience in the development, evaluation and application of novel tools for biomedical informatics research; and (2) by providing her training in biomedical informatics for clinical and translational research. Dr. Hoen proposes to participate in coursework, workshops, seminar series, and research meetings that focus on professional ethics, translational research methods, computational biology including genomics, metagenomics, network analysis, and systems biology. Dr. Hoen has assembled an exemplary mentoring team, led by Dr. Jason Moore, who has a longstanding history of mentorship, leadership, and funded research in biomedical informatics. Her team of mentors and advisors include internationally known experts on informatics methods development, network analysis and complex systems, computational analysis of metagenomic data, clinical and translational science, epidemiology and biomedical informatics leadership. The collective expertise embodied by this team will provide an outstanding resource for the development of Dr. Hoen's career and the successful execution of her multidisciplinary, translational research in biomedical informatics. Dr. Hoen's team is committed to ensuring that she achieves a successful mentored research and career development experience as she works toward independence within the timeframe of this award. Research Plan. The goal of the proposed research is to develop, evaluate and apply computational tools that capture the complexity of large, longitudinal datasets of microbial community composition in conjunction with rich clinical information from a unique ongoing large molecular epidemiologic study using a systems approach that focuses on the complex interactions between human hosts, the communities of bacterial taxa that comprise the microbiome, exposures, health and disease. The framework upon which this research will be built is a series of networks that represent the complex interactions between infants and microbial colonization patterns in light of early life exposures and health-related outcomes. The analyses proposed will address complex patterns captured by these networks including multi-scale associations, multi-way interactions between network components, and temporal dynamics in changing networks. The overarching hypothesis of this research is that these innovative approaches can reveal critical associations between microbiome composition and health and disease in early life. The translational potential of this research lies in novel opportunities to reduce disease risk through therapies that manipulate and preserve a healthy microbiome.